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<a href="_multi_variate_normal_distribution_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment"> *</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> *</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> * \brief       Implements a multi-variate normal distribution with zero mean.</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * </span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> *</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * \author      T.Voss, O.Krause</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \date        2016</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> *</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * </span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * </span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * </span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * </span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> *</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> */</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="preprocessor">#ifndef SHARK_STATISTICS_MULTIVARIATENORMALDISTRIBUTION_H</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="preprocessor">#define SHARK_STATISTICS_MULTIVARIATENORMALDISTRIBUTION_H</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#include &lt;<a class="code" href="_base_8h.html">shark/LinAlg/Base.h</a>&gt;</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#include &lt;<a class="code" href="_random_8h.html">shark/Core/Random.h</a>&gt;</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="comment"></span> </div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="comment">/// \brief Implements a multi-variate normal distribution with zero mean.</span></div>
<div class="foldopen" id="foldopen00040" data-start="{" data-end="};">
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html">   40</a></span><span class="comment"></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_multi_variate_normal_distribution.html" title="Implements a multi-variate normal distribution with zero mean.">MultiVariateNormalDistribution</a> {</div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="keyword">public</span>:<span class="comment"></span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment">    ///\brief Result type of a sampling operation.</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment">    /// </span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="comment">    /// The first element is the result of sampling this distribution, the</span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment">    /// second element is the original standard-normally distributed vector drawn</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">    /// for sampling purposes.</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment"></span>    <span class="keyword">typedef</span> std::pair&lt;RealVector,RealVector&gt; result_type;</div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment"></span> </div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">    /// \brief Constructor</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">    /// \param [in] Sigma covariance matrix</span></div>
<div class="foldopen" id="foldopen00051" data-start="{" data-end="}">
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a5617396a18a310cb513cf43d593f95de">   51</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a5617396a18a310cb513cf43d593f95de" title="Constructor.">MultiVariateNormalDistribution</a>(RealMatrix <span class="keyword">const</span>&amp; Sigma ) {</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span>        m_covarianceMatrix = Sigma;</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ad90c8cdf2257b5b523a38b0a36d95bf2" title="Calculates the evd of the current covariance matrix.">update</a>();</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span>    }</div>
</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span>    <span class="comment"></span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">    /// \brief Constructor</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a8e5899c265e936f1b7b5c77d77953620">   57</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a8e5899c265e936f1b7b5c77d77953620" title="Constructor.">MultiVariateNormalDistribution</a>(){} </div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span>    <span class="comment"></span></div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">    /// \brief Stores/Restores the distribution from the supplied archive.</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">    /// \param [in,out] ar The archive to read from/write to.</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">    /// \param [in] version Currently unused.</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">typename</span> Archive&gt;</div>
<div class="foldopen" id="foldopen00063" data-start="{" data-end="}">
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#ac2a3b0120928a80bc26a5a7df2ac2a1b">   63</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ac2a3b0120928a80bc26a5a7df2ac2a1b" title="Stores/Restores the distribution from the supplied archive.">serialize</a>( Archive &amp; ar, <span class="keyword">const</span> std::size_t version ) {</div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span>        ar &amp; BOOST_SERIALIZATION_NVP( m_covarianceMatrix );</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span>        ar &amp; BOOST_SERIALIZATION_NVP( m_decomposition );</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span>    }</div>
</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span><span class="comment"></span> </div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span><span class="comment">    /// \brief Resizes the distribution. Updates both eigenvectors and eigenvalues.</span></div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span><span class="comment">    /// \param [in] size The new size of the distribution</span></div>
<div class="foldopen" id="foldopen00070" data-start="{" data-end="}">
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a58c4c416f7e516ccd28dc53ae7828d78">   70</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a58c4c416f7e516ccd28dc53ae7828d78" title="Resizes the distribution. Updates both eigenvectors and eigenvalues.">resize</a>( std::size_t size ) {</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span>        m_covarianceMatrix = blas::identity_matrix&lt;double&gt;( size );</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ad90c8cdf2257b5b523a38b0a36d95bf2" title="Calculates the evd of the current covariance matrix.">update</a>();</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>    }</div>
</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span><span class="comment"></span> </div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span><span class="comment">    /// \brief Accesses the covariance matrix defining the distribution.</span></div>
<div class="foldopen" id="foldopen00076" data-start="{" data-end="}">
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#ab2f0af22ae2978225f6990f2abc01079">   76</a></span><span class="comment"></span>    RealMatrix <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ab2f0af22ae2978225f6990f2abc01079" title="Accesses the covariance matrix defining the distribution.">covarianceMatrix</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        <span class="keywordflow">return</span> m_covarianceMatrix;</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>    }</div>
</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>    <span class="comment"></span></div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span><span class="comment">    /// \brief Accesses a mutable reference to the covariance matrix </span></div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span><span class="comment">    /// defining the distribution. Allows for l-value semantics.</span></div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span><span class="comment">    /// </span></div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span><span class="comment">    /// ATTENTION: If the reference is altered, update needs to be called manually.</span></div>
<div class="foldopen" id="foldopen00084" data-start="{" data-end="}">
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#acf941923feae3b6de9845ce161e86d35">   84</a></span><span class="comment"></span>    RealMatrix&amp; <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#acf941923feae3b6de9845ce161e86d35" title="Accesses a mutable reference to the covariance matrix defining the distribution. Allows for l-value s...">covarianceMatrix</a>() {</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>        <span class="keywordflow">return</span> m_covarianceMatrix;</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>    }</div>
</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    <span class="comment"></span></div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span><span class="comment">    /// \brief Sets the covariance matrix and updates the internal variables. This is expensive</span></div>
<div class="foldopen" id="foldopen00089" data-start="{" data-end="}">
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a4908517c95357a454ceb2900be594a0c">   89</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a4908517c95357a454ceb2900be594a0c" title="Sets the covariance matrix and updates the internal variables. This is expensive.">setCovarianceMatrix</a>(RealMatrix <span class="keyword">const</span>&amp; matrix){</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ab2f0af22ae2978225f6990f2abc01079" title="Accesses the covariance matrix defining the distribution.">covarianceMatrix</a>() = matrix;</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ad90c8cdf2257b5b523a38b0a36d95bf2" title="Calculates the evd of the current covariance matrix.">update</a>();</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>    }</div>
</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span><span class="comment"></span> </div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span><span class="comment">    /// \brief Accesses an immutable reference to the eigenvectors of the covariance matrix.</span></div>
<div class="foldopen" id="foldopen00095" data-start="{" data-end="}">
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#aa1a79af05867366d0ca300825a29a87a">   95</a></span><span class="comment"></span>    RealMatrix <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#aa1a79af05867366d0ca300825a29a87a" title="Accesses an immutable reference to the eigenvectors of the covariance matrix.">eigenVectors</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>        <span class="keywordflow">return</span> m_decomposition.Q();</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>    }</div>
</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span><span class="comment"></span> </div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span><span class="comment">    /// \brief Accesses an immutable reference to the eigenvalues of the covariance matrix.</span></div>
<div class="foldopen" id="foldopen00100" data-start="{" data-end="}">
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a304ff217e3a7ad935387e7a92b67546e">  100</a></span><span class="comment"></span>    RealVector <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a304ff217e3a7ad935387e7a92b67546e" title="Accesses an immutable reference to the eigenvalues of the covariance matrix.">eigenValues</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>        <span class="keywordflow">return</span> m_decomposition.D();</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>    }</div>
</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span><span class="comment"></span> </div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span><span class="comment">    /// \brief Samples the distribution.</span></div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span><span class="comment">    /// \param [in] rng Random number generator.</span></div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> randomType&gt;</div>
<div class="foldopen" id="foldopen00107" data-start="{" data-end="}">
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#a11520c6c68f92492b1b559000b8fdbbe">  107</a></span>    result_type <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a11520c6c68f92492b1b559000b8fdbbe" title="Samples the distribution.">operator()</a>(randomType&amp; rng)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>        RealVector z( m_covarianceMatrix.size1() );</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        </div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>        <span class="keywordflow">for</span>( std::size_t i = 0; i &lt; z.size(); i++ ) {</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>            z( i ) = <a class="code hl_function" href="namespaceshark_1_1random.html#a972c5f7f031612a130aa077fc9136a9f" title="Draws a number from the normal distribution with given mean and variance by drawing random numbers fr...">random::gauss</a>(rng, 0., 1. );</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>        }</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>        </div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>        RealVector result = m_decomposition.Q() % to_diagonal(sqrt(max(<a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#a304ff217e3a7ad935387e7a92b67546e" title="Accesses an immutable reference to the eigenvalues of the covariance matrix.">eigenValues</a>(),0))) % z;</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        <span class="keywordflow">return</span> std::make_pair( result, z );</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>    }       </div>
</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span><span class="comment"></span> </div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span><span class="comment">    /// \brief Calculates the evd of the current covariance matrix.</span></div>
<div class="foldopen" id="foldopen00119" data-start="{" data-end="}">
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution.html#ad90c8cdf2257b5b523a38b0a36d95bf2">  119</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution.html#ad90c8cdf2257b5b523a38b0a36d95bf2" title="Calculates the evd of the current covariance matrix.">update</a>() {</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>        m_decomposition.decompose(m_covarianceMatrix);</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>    }</div>
</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span> </div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>    RealMatrix m_covarianceMatrix; <span class="comment">///&lt; Covariance matrix of the mutation distribution.</span></div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>    blas::symm_eigenvalue_decomposition&lt;RealMatrix&gt; m_decomposition; <span class="comment">/// &lt; Eigenvalue decomposition of the covarianceMatrix</span></div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>};</div>
</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span><span class="comment"></span> </div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span><span class="comment">/// \brief Multivariate normal distribution with zero mean using a cholesky decomposition</span></div>
<div class="foldopen" id="foldopen00129" data-start="{" data-end="};">
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html">  129</a></span><span class="comment"></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html" title="Multivariate normal distribution with zero mean using a cholesky decomposition.">MultiVariateNormalDistributionCholesky</a>{</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span><span class="keyword">public</span>:<span class="comment"></span></div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span><span class="comment">    /// \brief Result type of a sampling operation.</span></div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span><span class="comment">    /// </span></div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span><span class="comment">    /// The first element is the result of sampling this distribution, the</span></div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span><span class="comment">    /// second element is the original standard-normally distributed vector drawn</span></div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span><span class="comment">    /// for sampling purposes.</span></div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment"></span>    <span class="keyword">typedef</span> std::pair&lt;RealVector,RealVector&gt; result_type;</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="comment"></span> </div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span><span class="comment">    /// \brief Constructor</span></div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span><span class="comment">    /// \param [in] covariance Covariance matrix.</span></div>
<div class="foldopen" id="foldopen00140" data-start="{" data-end="}">
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7133de09b7605c17d9f0caa1dff6de58">  140</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7133de09b7605c17d9f0caa1dff6de58" title="Constructor.">MultiVariateNormalDistributionCholesky</a>( RealMatrix <span class="keyword">const</span>&amp; <a class="code hl_function" href="namespaceshark.html#a0596df3c2544cbca51ec485254c27448" title="Calculates the covariance matrix of the data vectors.">covariance</a>){</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7eea13a233895d60e0ab27837f5f2e7c" title="Sets the new covariance matrix by computing the new cholesky dcomposition.">setCovarianceMatrix</a>(<a class="code hl_function" href="namespaceshark.html#a0596df3c2544cbca51ec485254c27448" title="Calculates the covariance matrix of the data vectors.">covariance</a>);</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>    }</div>
</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>    </div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7c07e530a9cf3007a0e56b49042484e1">  144</a></span>    <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7c07e530a9cf3007a0e56b49042484e1">MultiVariateNormalDistributionCholesky</a>(){} </div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>    <span class="comment"></span></div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span><span class="comment">    /// \brief Stores/Restores the distribution from the supplied archive.</span></div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span><span class="comment">    ///\param [in,out] ar Archive to read from/write to.</span></div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span><span class="comment">    ///\param [in] version Currently unused.</span></div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">typename</span> Archive&gt;</div>
<div class="foldopen" id="foldopen00150" data-start="{" data-end="}">
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac82104835bfa8ccecae3bfc313d5a863">  150</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac82104835bfa8ccecae3bfc313d5a863" title="Stores/Restores the distribution from the supplied archive.">serialize</a>( Archive &amp; ar, <span class="keyword">const</span> std::size_t version ) {</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>        ar &amp; BOOST_SERIALIZATION_NVP( m_cholesky);</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>    }</div>
</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span><span class="comment"></span> </div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span><span class="comment">    /// \brief Resizes the distribution. Updates both eigenvectors and eigenvalues.</span></div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span><span class="comment">    /// \param [in] size The new size of the distribution</span></div>
<div class="foldopen" id="foldopen00156" data-start="{" data-end="}">
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a3282df396618643594c4e4e5ea932862">  156</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a3282df396618643594c4e4e5ea932862" title="Resizes the distribution. Updates both eigenvectors and eigenvalues.">resize</a>( std::size_t <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a> ) {</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>        m_cholesky = blas::identity_matrix&lt;double&gt;( <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a> );</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>    }</div>
</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>    <span class="comment"></span></div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span><span class="comment">    /// \brief Returns the size of the created vectors</span></div>
<div class="foldopen" id="foldopen00161" data-start="{" data-end="}">
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066">  161</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>        <span class="keywordflow">return</span> m_cholesky.lower_factor().size1();</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>    }</div>
</div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span><span class="comment"></span> </div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span><span class="comment">    /// \brief Returns the matrix holding the lower cholesky factor A</span></div>
<div class="foldopen" id="foldopen00166" data-start="{" data-end="}">
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac47101432c4252ea0a86ae4e622cb69a">  166</a></span><span class="comment"></span>    blas::matrix&lt;double,blas::column_major&gt; <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ac47101432c4252ea0a86ae4e622cb69a" title="Returns the matrix holding the lower cholesky factor A.">lowerCholeskyFactor</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span>        <span class="keywordflow">return</span> m_cholesky.lower_factor();</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>    }</div>
</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span> </div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>    <span class="comment"></span></div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span><span class="comment">    /// \brief Sets the new covariance matrix by computing the new cholesky dcomposition</span></div>
<div class="foldopen" id="foldopen00172" data-start="{" data-end="}">
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7eea13a233895d60e0ab27837f5f2e7c">  172</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7eea13a233895d60e0ab27837f5f2e7c" title="Sets the new covariance matrix by computing the new cholesky dcomposition.">setCovarianceMatrix</a>(RealMatrix <span class="keyword">const</span>&amp; matrix){</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>        m_cholesky.decompose(matrix);</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>    }</div>
</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span><span class="comment"></span> </div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span><span class="comment">    /// \brief Updates the covariance matrix of the distribution to C&lt;- alpha*C+beta * vv^T</span></div>
<div class="foldopen" id="foldopen00177" data-start="{" data-end="}">
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ab0afb717b2e773692a4b972c104708d1">  177</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#ab0afb717b2e773692a4b972c104708d1" title="Updates the covariance matrix of the distribution to C&lt;- alpha*C+beta * vv^T.">rankOneUpdate</a>(<span class="keywordtype">double</span> alpha, <span class="keywordtype">double</span> beta, RealVector <span class="keyword">const</span>&amp; v){</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>        m_cholesky.update(alpha,beta,v);</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>    }</div>
</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>    </div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> randomType, <span class="keyword">class</span> Vector1, <span class="keyword">class</span> Vector2&gt;</div>
<div class="foldopen" id="foldopen00182" data-start="{" data-end="}">
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a8653eefd19a56f858fd24c3d2b948284">  182</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a8653eefd19a56f858fd24c3d2b948284">generate</a>(randomType&amp; rng, Vector1&amp; y, Vector2&amp; z)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>        z.resize(<a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a>());</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>        y.resize(<a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a>());</div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>        <span class="keywordflow">for</span>( std::size_t i = 0; i != <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a9fb3ed174bf3586b31d60b4113dde066" title="Returns the size of the created vectors.">size</a>(); i++ ) {</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>            z( i ) = <a class="code hl_function" href="namespaceshark_1_1random.html#a972c5f7f031612a130aa077fc9136a9f" title="Draws a number from the normal distribution with given mean and variance by drawing random numbers fr...">random::gauss</a>(rng, 0, 1 );</div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>        }</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>        noalias(y) = blas::triangular_prod&lt;blas::lower&gt;(m_cholesky.lower_factor(),z);</div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span>    }</div>
</div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span><span class="comment"></span> </div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span><span class="comment">    /// \brief Samples the distribution.</span></div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span><span class="comment">    /// Returns a vector pair (y,z) where  y=Lz and, L is the lower cholesky factor and z is a vector</span></div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span><span class="comment">    /// of normally distributed numbers. Thus y is the real sampled point.</span></div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span><span class="comment">    /// \param [in] rng Random number generator.</span></div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> randomType&gt;</div>
<div class="foldopen" id="foldopen00198" data-start="{" data-end="}">
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno"><a class="line" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a1de3800a44132fead861550cfb36a038">  198</a></span>    result_type <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a1de3800a44132fead861550cfb36a038" title="Samples the distribution.">operator()</a>(randomType&amp; rng)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>        result_type result;</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span>        RealVector&amp; z = result.second;</div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>        RealVector&amp; y = result.first;</div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>        <a class="code hl_function" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a8653eefd19a56f858fd24c3d2b948284">generate</a>(rng,y,z);</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>        <span class="keywordflow">return</span> result;</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>    }</div>
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<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span> </div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>    blas::cholesky_decomposition&lt;blas::matrix&lt;double,blas::column_major&gt; &gt; m_cholesky; <span class="comment">///&lt; The lower cholesky factor (actually any is okay as long as it is the left)</span></div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>};</div>
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<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span> </div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span> </div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>}</div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span> </div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span><span class="preprocessor">#endif</span></div>
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